path

import data

read_as_df <- function(path, col_name) {
  df <- read.csv(path, header = FALSE) %>% data.frame()
  names(df) <- col_name
  return(df)
}

points <- read.csv("data/cpp_astar_path.csv")
points_pick_reg <- read.csv("data/cpp_reg_simplified.csv")
three_d_map <- read.csv("data/status.csv")

head(points)

##   x y z
## 1 1 1 1
## 2 2 2 2
## 3 3 3 3
## 4 4 4 4
## 5 5 5 5
## 6 6 6 6

points_pick_reg

##     x  y  z
## 1   1  1  1
## 2  35 35 35
## 3  39 38 39
## 4  43 38 43
## 5  47 38 47
## 6  50 39 50
## 7  51 50 61
## 8  32 68 80
## 9  29 69 83
## 10 21 76 91
## 11 17 77 95
## 12 10 80 98

plot using plotly package

print_points <- function(input_df){
  return (input_df %>% 
            plot_ly() %>% 
            add_paths(x = ~x, y = ~y, z = ~z))
}

print_points(points)

print_points(points_pick_reg)

visiualization with searched areas and blocked areas.

map_block <- three_d_map %>% filter(status == 1)
map_searched <- three_d_map %>% filter(status == 2)

p <- plot_ly() %>%
  # draw blocked
  add_trace(type="scatter3d", mode = 'markers', ids = 'blocks',
            x = map_block$x, y = map_block$y, z = map_block$z, 
            marker = list(color = c('#696969'), 
                          symbol = 'square', size = '2', opacity = '0.5')) %>% 
  # draw searched
  add_trace(type="scatter3d", mode = 'markers', ids = 'blocks',
            x = map_searched$x, y = map_searched$y, z = map_searched$z, 
            marker = list(color = c('#66ccff'), 
                          symbol = 'square', size = '0.2', opacity = '1')) %>% 
  
  add_paths(x = points_pick_reg$x, y = points_pick_reg$y, z = points_pick_reg$z,
            line = list(width = 10, color = '#FF0000'))
p